iPhone 16 Pro Max
Geekbench AI Score
4682
Single Precision Score
32859
Half Precision Score
45439
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | January 28 2025 09:36 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2.1 |
| Model | iPhone 16 Pro Max |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2023
376.3 IPS |
|
|
Image Classification (HP)
|
100% |
15045
2.80 KIPS |
|
|
Image Classification (Q)
|
97% |
19217
3.59 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1967
31.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
18304
296.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
24005
389.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
9663
11.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
155064
180.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
294848
345.6 IPS |
|
|
Object Detection (SP)
|
100% |
2225
176.5 IPS |
|
|
Object Detection (HP)
|
100% |
16347
1.30 KIPS |
|
|
Object Detection (Q)
|
91% |
22411
1.79 KIPS |
|
|
Face Detection (SP)
|
100% |
3703
44.0 IPS |
|
|
Face Detection (HP)
|
100% |
41072
488.0 IPS |
|
|
Face Detection (Q)
|
100% |
56621
672.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
8171
63.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
95354
734.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
160866
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
25048
32.2 IPS |
|
|
Style Transfer (HP)
|
100% |
246163
316.4 IPS |
|
|
Style Transfer (Q)
|
96% |
301940
389.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5838
215.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52421
1.94 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
86372
3.19 KIPS |
|
|
Text Classification (SP)
|
100% |
3504
4.68 KIPS |
|
|
Text Classification (HP)
|
100% |
4435
5.92 KIPS |
|
|
Text Classification (Q)
|
93% |
4500
6.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
3824
65.9 IPS |
|
|
Machine Translation (HP)
|
100% |
9379
161.6 IPS |
|
|
Machine Translation (Q)
|
98% |
11518
199.0 IPS |
